近年來隨著網路科技和資訊技術的快速發展,網際網路的使用變得愈來愈普遍,進而使得上網人口持續不斷的攀升,創造出巨大的網路商機,也讓各大企業爭食這塊發展潛力驚人的大餅,造就了線上購物網站如雨後春筍般的成立,成為許多公司積極投入經營的一項重要活動。 目前國內各式各樣的購物網站中,有許多網站中提供了玲瑯滿目的商品,然而在這麼大量的商品中,消費者如何快速且正確的找到所需的產品成為一重要的課題。消費者在網路購物過程中所遭遇的困難,其中在產品搜尋上,經常會發生產品的分類與消費者的分類認知不同,造成搜尋上的困擾;或是產品歸類方式不一致、歸類錯誤、不易理解,因此,如何運用以消費者為中心的概念,去產生出符合消費者認知購物網站的產品分類,為本研究之主題。本研究運用了卡片分類法,去產生以使用者為中心的產品分類,並利用其產生出的產品分類與現今某知名購物網站之產品分類進行產品搜尋時間、點擊次數和平均點擊時間之比較,實驗結果發現以使用者為中心的產品分類,在搜尋相同的產品下,能夠減少產品搜尋的搜尋時間、點擊次數和平均點擊時間,進而提升使用者搜尋產品的效率,實驗結果將能對日後購物網站產品分類有所助益。
Nowadays, as the technology of internet and information exchange develops rapidly, the use of internet has become more common. The continuous increase of the number of those who use internet therefore creates tremendous opportunities for online business and results in a fierce competition between many leading companies for this commercial opportunity. Furthermore, the idea of running an online business has accelerated the establishment of many online shopping websites. Many domestic online shopping website have provided a range of different products. The problem is, how can consumers find what they need correctly and promptly. The difficulties that consumers may meet during online shopping may be: having different understandings about the categories of the products they want, or having difficulties finding the correct category due to unsynchronized or incorrect categorization. Hence we see an outstanding problem, how can we categorize products from the user-centered perspective so that consumers can easily recognize them. This research has used card sorting to produce a set of categories of products so that the consumers can easily find the products they want. Furthermore, the resulting product categorization has been compared with the product categorization that has been used by a well known online shopping website on the duration of product searching, number of clicks and average clicking duration. It has been evident that the user-centered product categorization has effectively reduced the duration of product searching, number of clicks and average clicking duration, and eventually has increased the efficiency of product searching for consumers when making a search for a specific product. The experimental result will effectively improve the online shopping product categorization in the future.